On the design and implementation of a control system processor

In general digital control algorithms are multi-input multi-output (MIMO) recursive digital filters, but there are particular numerical requirements in control system processing for which standard processor devices are not well suited, in particular arising in systems with high sample rates. There is therefore a clear need to understand the numerical requirements properly, to identity optimised forms for implementing control laws, and to translate these into efficient processor architectures. By taking a considered view of the numerical and calculation requirements of control algorithms, it is possible to consider special purpose processors that provide well-targeted support of control laws. This thesis describes a compact, high-speed, special-purpose processor which offers a low-cost solution to implementing linear time invariant controllers. [Continues.

Neuro-fuzzy software for intelligent control and education

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Major Automação). Faculdade de Engenharia. Universidade do Porto. 200

Doubly-fed induction generator used in wind energy

Wound-rotor induction generator has numerous advantages in wind power generation over other generators. One scheme for wound-rotor induction generator is realized when a converter cascade is used between the slip-ring terminals and the utility grid to control the rotor power. This configuration is called the doubly-fed induction generator (DFIG). In this work, a novel induction machine model is developed. This model includes the saturation in the main and leakage flux paths. It shows that the model which considers the saturation effects gives more realistic results. A new technique, which was developed for synchronous machines, was applied to experimentally measure the stator and rotor leakage inductance saturation characteristics on the induction machine. A vector control scheme is developed to control the rotor side voltage-source converter. Vector control allows decoupled or independent control of both active and reactive power of DFIG. These techniques are based on the theory of controlling the B- and q- axes components of voltage or current in different reference frames. In this work, the stator flux oriented rotor current control, with decoupled control of active and reactive power, is adopted. This scheme allows the independent control of the generated active and reactive power as well as the rotor speed to track the maximum wind power point. Conventionally, the controller type used in vector controllers is of the PI type with a fixed proportional and integral gain. In this work, different intelligent schemes by which the controller can change its behavior are proposed. The first scheme is an adaptive gain scheduler which utilizes different characteristics to generate the variation in the proportional and the integral gains. The second scheme is a fuzzy logic gain scheduler and the third is a neuro-fuzzy controller. The transient responses using the above mentioned schemes are compared analytically and experimentally. It has been found that although the fuzzy logic and neuro-fuzzy schemes are more complicated and have many parameters; this complication provides a higher degree of freedom in tuning the controller which is evident in giving much better system performance. Finally, the simulation results were experimentally verified by building the experimental setup and implementing the developed control schemes

Development of an electrochemical micromachining (μECM) machine

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.Electrochemical machining (ECM) and especially electrochemical micromachining (μECM) became an attractive area of research due to the fact that this process does not create any defective layer after machining and that there is a growing demand for better surface integrity on different micro applications such as microfluidics systems and stressfree drilled holes in the automotive and aerospace sectors. Electrochemical machining is considered as a non-conventional machining process based on the phenomenon of electrolysis. This process requires maintaining a small gap - the interelectrode gap (IEG) - between the anode (workpiece) and the cathode (tool-electrode) in order to achieve acceptable machining results (i.e. accuracy, high aspect ratio with appropriate material removal rate and efficiency). This work presents the design of a next generation μECM machine for the automotive, aerospace, medical and metrology sectors. It has 3 axes of motion (X, Y and Z) and a spindle allowing the tool-electrode to rotate during machining. The linear slides for each axis use air bearings with linear DC brushless motors and 2nmresolution encoders for ultra-precise motion. The control system is based on the Power PMAC motion controller from Delta Tau. The electrolyte tank is located at the rear of the machine and allows the electrolyte to be changed quickly. A pulse power supply unit (PSU) and a special control algorithm have been implemented. The pulse power supply provides not only ultra-short pulses (50ns), but also plus and minus biases as well as a polarity switching functionality. It fulfils the requirements of tool preparation with reversed ECM on the machine. Moreover, the PSU is equipped with an ultrafast over current protection which prevents the tool-electrode from being damaged in case of short-circuits. Two different process control algorithms were made: one is fuzzy logic based and the other is adapting the feed rate according to the position and time at which short-circuits were detected. The developed machine is capable of drilling micro holes in hard-to-machine materials but also machine micro-styli and micro-needles for the metrology (micro CMM) and medical sectors. This work also presents drilling trials performed with the machine with an orbiting tool. Machining experiments were also carried out using electrolytes made of a combination of HCl and NaNO aqueous solutions. The developed machine was used to fabricate micro tools out of 170μm WC-Co alloy shafts via micro electrochemical turning and drill deep holes via μECM in disks made of 18NiCr6 alloy. Results suggest that this process can be used for industrial applications for hard-to-machine materials. The author also suggests that the developed machine can be used to manufacture micro-probes and micro-tools for metrology and micro-manufacturing purposes.Brunel University European Commissio

Neuromorphic, Digital and Quantum Computation with Memory Circuit Elements

Memory effects are ubiquitous in nature and the class of memory circuit elements - which includes memristors, memcapacitors and meminductors - shows great potential to understand and simulate the associated fundamental physical processes. Here, we show that such elements can also be used in electronic schemes mimicking biologically-inspired computer architectures, performing digital logic and arithmetic operations, and can expand the capabilities of certain quantum computation schemes. In particular, we will discuss few examples where the concept of memory elements is relevant to the realization of associative memory in neuronal circuits, spike-timing-dependent plasticity of synapses, digital and field-programmable quantum computing

Multiple configuration shell-core structured robotic manipulator with interchangeable mechatronic joints : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Engineering in Mechatronics at Massey University, Turitea Campus, Palmerston North, New Zealand

With the increase of robotic technology utilised throughout industry, the need for skilled labour in this area has increased also. As a result, education dealing with robotics has grown at both the high-school and tertiary educational level. Despite the range of pedagogical robots currently on the market, there seems to be a low variety of these systems specifically related to the types of robotic manipulator arms popular for industrial applications. Furthermore, a fixed-arm system is limited to only serve as an educational supplement for that specific configuration and therefore cannot demonstrate more than one of the numerous industrial-type robotic arms. The Shell-Core structured robotic manipulator concept has been proposed to improve the quality and variety of available pedagogical robotic arm systems on the market. This is achieved by the reconfigurable nature of the concept, which incorporates shell and core structural units to make the construction of at least 5 mainstream industrial arms possible. The platform will be suitable, but not limited to use within the educational robotics industry at high-school and higher educational levels and may appeal to hobbyists. Later dubbed SMILE (Smart Manipulator with Interchangeable Links and Effectors), the system utilises core units to provide either rotational or linear actuation in a single plane. A variety of shell units are then implemented as the body of the robotic arm, serving as appropriate offsets to achieve the required configuration. A prototype consisting of a limited number of ‘building blocks’ was developed for proof-of-concept, found capable of achieving several of the proposed configurations. The outcome of this research is encouraging, with a Massey patent search confirming the unique features of the proposed concept. The prototype system is an economic, easy to implement, plug and play, and multiple-configuration robotic manipulator, suitable for various applications

FPGAs in Industrial Control Applications

The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs

High efficiency smart voltage regulating module for green mobile computing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis a design for a smart high efficiency voltage regulating module capable of supplying the core of modern microprocessors incorporating dynamic voltage and frequency scaling (DVS) capability is accomplished using a RISC based microcontroller to facilitate all the functions required to control, protect, and supply the core with the required variable operating voltage as set by the DVS management system. Normally voltage regulating modules provide maximum power efficiency at designed peak load, and the efficiency falls off as the load moves towards lesser values. A mathematical model has been derived for the main converter and small signal analysis has been performed in order to determine system operation stability and select a control scheme that would improve converter operation response to transients and not requiring intense computational power to realize. A Simulation model was built using Matlab/Simulink and after experimenting with tuned PID controller and fuzzy logic controllers, a simple fuzzy logic control scheme was selected to control the pulse width modulated converter and several methods were devised to reduce the requirements for computational power making the whole system operation realizable using a low power RISC based microcontroller. The same microcontroller provides circuit adaptations operation in addition to providing protection to load in terms of over voltage and over current protection. A novel circuit technique and operation control scheme enables the designed module to selectively change some of the circuit elements in the main pulse width modulated buck converter so as to improve efficiency over a wider range of loads. In case of very light loads as the case when the device goes into standby, sleep or hibernation mode, a secondary converter starts operating and the main converter stops. The secondary converter adapts a different operation scheme using switched capacitor technique which provides high efficiency at low load currents. A fuzzy logic control scheme was chosen for the main converter for its lighter computational power requirement promoting implementation using ultra low power embedded controllers. Passive and active components were carefully selected to augment operational efficiency. These aspects enabled the designed voltage regulating module to operate with efficiency improvement in off peak load region in the range of 3% to 5%. At low loads as the case when the computer system goes to standby or sleep mode, the efficiency improvent is better than 13% which will have noticeable contribution in extending battery run time thus contributing to lowering the carbon footprint of human consumption

Accuracy versus simplicity in online battery model identification

This paper presents a framework for battery modeling in online, real-time applications where accuracy is important but speed is the key. The framework allows users to select model structures with the smallest number of parameters that is consistent with the accuracy requirements of the target application. The tradeoff between accuracy and speed in a battery model identification process is explored using different model structures and parameter-fitting algorithms. Pareto optimal sets are obtained, allowing a designer to select an appropriate compromise between accuracy and speed. In order to get a clearer understanding of the battery model identification problem, “identification surfaces” are presented. As an outcome of the battery identification surfaces, a new analytical solution is derived for battery model identification using a closed-form formula to obtain a battery’s ohmic resistance and open circuit voltage from measurement data. This analytical solution is used as a benchmark for comparison of other fitting algorithms and it is also used in its own right in a practical scenario for state-of-charge estimation. A simulation study is performed to demonstrate the effectiveness of the proposed framework and the simulation results are verified by conducting experimental tests on a small NiMH battery pack